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Doghouse Diaries

13 Graphs for Laughs

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Doghouse Diaries

Can graphs be funny? That’s a silly question, as you’ve seen plenty of funny flowcharts, pie charts, and Venn diagrams, as well as other charts and graphs, made just for fun here already. But there are other kinds of charts that have a joke in them somewhere. Doghouse Diaries explains a graph's potential for humor. This type of chart is called an XY Plot, or scatter chart, which places items along two axes depending on the two variables measured in relationship to other items.

Randall Munroe of xkcd made a scatter plot comparing the tastiness of fruits with the difficulty of preparing and eating them. The comic has a NSFW title.

This graph sparked a bit of controversy, as both tastiness and difficulty are opinions, and inspired another graph from R. Stevens, a grapefruit lover.

The kind of graph that is the most familiar to most people is the line graph that plots the rise and fall of one variable over time. It’s easier to understand when the peaks and valleys are labeled accordingly. Here we see the highs and lows of being a young man.

One you may relate to this time of year is the vacation graph by Jorge Cham of PHD Comics. The stress that goes into arranging a vacation pretty much negates the stress relief you get from being on a vacation, and then you have to deal with all the problems that cropped up in your absence. Is it worth it? Yes, for the stories you’ll have to tell about it for the rest of your life.

Graphic artist Stephen Wildish creates clever posters and graphics of all kinds. One form he uses is the narrative graph, which plots stories, more than one at a time, in order to compare them. This one called Common Nanny Narratives has the three nanny stories we are most familiar with. They are obviously familiar with each other as well. Also see his Common Fairytale Narratives, three of them, and the Hamlet/Lion King graph.

Wildish also does Venn diagrams, mostly of food, but no subject is off-limits. Favorite foods are often made of three or four main flavor ingredients, and can be broken down into their components, like this diagram of sauces. See more of Wildish’s Venn diagrams here, and buy one at Red Bubble. See Wildish’s full range of graphics at his website

A Gantt chart is a type of timeline, often used for projects, in which different elements each have their own timeline, but they are all coordinated. When I first read about them, I thought these would be perfect for explaining to my kids how to cook several dishes and get them to the dinner table at the same time. The Universal Gantt Chart for Project Managers shows how projects actually go, instead of how they are planned.

A simpler example is this Gantt chart by Bridget Finnegan detailing what interested her during childhood. You can see her baby brother was only interesting for a short time, while only mommy predated her interest in Barbie.

Timelines can be confusing in movies, and none as much as the time-travel film Primer. Although the movie covers only five days, there are nine timelines, according to this graph at Unreality magazine. Click the image at Unreality twice to enlarge it to readable size. While this is a serious attempt to make sense of the movie, it is way more trouble than it’s worth even to read it. I can imagine the torture that went into constructing it.

Still, it’s an improvement over the Primer timeline from Randall Munroe at xkcd, a small part of a comic that has several movie timelines. The others are pretty straightforward.

Then there are pie charts. You’d think that pie charts would be so easy to understand, but there’s always someone who doesn’t get it. See more pie charts in a previous list.

If you don’t like any charts at all, may I suggest the Grapathy Shirt, for those who are sick of graphs.

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Scientists Think They Know How Whales Got So Big
May 24, 2017
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It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]